Reliability of brain atrophy measurements in multiple sclerosis using MRI: an assessment of six freely available software packages for cross-sectional analyses.

Purpose: Volume measurement using MRI is important to assess brain atrophy in multiple sclerosis (MS). However, differences between scanners, acquisition protocols, and analysis software introduce unwanted variability of volumes. To quantify theses effects, we compared within-scanner repeatability a...

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Publicado en:Neuroradiology Vol. 65; no. 10; pp. 1459 - 1473
Autores principales: van Nederpelt, David R., Amiri, Houshang, Brouwer, Iman, Noteboom, Samantha, Mokkink, Lidwine B., Barkhof, Frederik, Vrenken, Hugo, Kuijer, Joost P. A.
Formato: diagnostic images research tables/charts Journal Article
Publicado: Springer Nature Oct2023
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2023
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00234-023-03189-8
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        atl: Reliability of brain atrophy measurements in multiple sclerosis using MRI: an assessment of six freely available software packages for cross-sectional analyses.
      aug:
        au:
          van Nederpelt, David R.
          Amiri, Houshang
          Brouwer, Iman
          Noteboom, Samantha
          Mokkink, Lidwine B.
          Barkhof, Frederik
          Vrenken, Hugo
          Kuijer, Joost P. A.
        affil: MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
      sug:
        subj:
          Multiple Sclerosis Pathology
          Magnetic Resonance Imaging Methods
          Brain Diseases Pathology
          Atrophy Pathology
          Image Processing, Computer Assisted Methods
          Interrater Reliability Evaluation
          Human
          Cross Sectional Studies
          Comparative Studies
          Software
          Descriptive Statistics
          Intraclass Correlation Coefficient
          Interrater Reliability
          Funding Source
          Gray Matter Pathology
          White Matter Pathology
      ab: Purpose: Volume measurement using MRI is important to assess brain atrophy in multiple sclerosis (MS). However, differences between scanners, acquisition protocols, and analysis software introduce unwanted variability of volumes. To quantify theses effects, we compared within-scanner repeatability and between-scanner reproducibility of three different MR scanners for six brain segmentation methods. Methods: Twenty-one people with MS underwent scanning and rescanning on three 3 T MR scanners (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) to obtain 3D T1-weighted images. FreeSurfer, FSL, SAMSEG, FastSurfer, CAT-12, and SynthSeg were used to quantify brain, white matter and (deep) gray matter volumes both from lesion-filled and non-lesion-filled 3D T1-weighted images. We used intra-class correlation coefficient (ICC) to quantify agreement; repeated-measures ANOVA to analyze systematic differences; and variance component analysis to quantify the standard error of measurement (SEM) and smallest detectable change (SDC). Results: For all six software, both between-scanner agreement (ICCs ranging 0.4–1) and within-scanner agreement (ICC range: 0.6–1) were typically good, and good to excellent (ICC > 0.7) for large structures. No clear differences were found between filled and non-filled images. However, gray and white matter volumes did differ systematically between scanners for all software (p < 0.05). Variance component analysis yielded within-scanner SDC ranging from 1.02% (SAMSEG, whole-brain) to 14.55% (FreeSurfer, CSF); and between-scanner SDC ranging from 4.83% (SynthSeg, thalamus) to 29.25% (CAT12, thalamus). Conclusion: Volume measurements of brain, GM and WM showed high repeatability, and high reproducibility despite substantial differences between scanners. Smallest detectable change was high, especially between different scanners, which hampers the clinical implementation of atrophy measurements.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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